Fault diagnosis of excavator hydraulic system based on partial least squares regression

In order to improve the reliability of the excavator's hydraulic system, a fault diagnosis approach based on partial least squares regression (PLSR) was proposed. The principal of the method was as follows: Firstly, nonlinear iterative partial least squares (NIPALS) algorithm was applied to compute components and the optimal number of components was determined by the total variance explained. As a result, an input-output PLSR model was established. Secondly, generalized likelihood ratio (GLR) test performed a hypothesis test for model residual so as to identify the system faults. The experimental results show that all the test faults are correctly identified, and it can be used in the fault diagnosis.